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How Do People Evaluate Foreign Aid To ‘Nasty’ Regimes?

Published online by Cambridge University Press:  28 February 2018

Tobias Heinrich  and
Yoshiharu Kobayashi
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Abstract

Recent theories of foreign aid assume that moral motives drive voters’ preferences about foreign aid. However, little is known about how moral concerns interact with the widely accepted instrumental goals that aid serves. Moreover, what effects does this interplay have on preferences over policy actions? This article assesses these questions using a survey experiment in which respondents evaluate foreign aid policies toward nasty recipient regimes (those that violate human rights, rig elections, crack down on media, etc.). The results indicate that the public does have a strong aversion to providing aid to nasty recipient regimes, but that it also appreciates the instrumental benefits that aid helps acquire. Contrary to a mainstay assertion in the literature, the study finds that moral aversion can largely be reversed if the donor government engages more with the nasty country. These findings call into question the micro-foundations of recent theories of foreign aid, and produce several implications for the aid literature.

Keywords

international developmentaidhuman rightpublic opinionmorality
Type
Articles
Information
British Journal of Political Science , Volume 50 , Issue 1 , January 2020 , pp. 103 - 127
Copyright
© Cambridge University Press 2018 

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Footnotes

*

Department of Political Science, University of South Carolina (email: heinrict@mailbox.sc.edu); Department of Political Science and International Relations, Nazarbayev University (email: yoshiharu.kobayashi@gmail.com). Authors’ names are listed alphabetically. Both authors have contributed equally to the article. We are grateful for comments from the four anonymous reviewers and participants at the 2015 MPSA, 110th APSA Annual Meeting (2014), 2014 KUBEC workshop, 4th Annual General Conference of the European Political Science Association (2014), and in particular from Daina Chiba, Simone Dietrich, Shu-Shan Lee, Sonja Grimm, Carla Martinez Machain, Han Dorussen, Tom Scotto, Randy Stevenson, Christina Schneider, Atsushi Tago, Mike Tierney, Dan Tirone, Teppei Yamamoto, Tim Peterson and Cliff Morgan. We also wish to thank Max Hilbig for help with executing the survey experiment and Thomas Leeper for dealing with Amazon’s MTurk. Data replication sets are available in Harvard Dataverse at: https://dx.doi.org/doi:10.7910/DVN/TKTN5J and online appendices are available at: https://doi.org/10.1017/S0007123417000503.

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